{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Yellowbrick Text Examples \n",
    "\n",
    "This notebook is a sample of the text visualizations that yellowbrick provides"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import sys \n",
    "\n",
    "# Modify the path \n",
    "sys.path.append(\"..\")\n",
    "\n",
    "import yellowbrick as yb \n",
    "import matplotlib.pyplot as plt "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Text Corpus for Example Code\n",
    "\n",
    "Yellowbrick has provided a text corpus wrangled from the [Baleen RSS Corpus](http://baleen.districtdatalabs.com/) to present the following examples. If you haven't downloaded the data, you can do so by running:\n",
    "\n",
    "```\n",
    "$ python download.py\n",
    "```\n",
    "\n",
    "In the same directory as the text notebook. Note that this will create a directory called `data` that contains subdirectories with the provided datasets. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from download import download_all \n",
    "from sklearn.datasets.base import Bunch\n",
    "\n",
    "## The path to the test data sets\n",
    "FIXTURES  = os.path.join(os.getcwd(), \"data\")\n",
    "\n",
    "## Dataset loading mechanisms\n",
    "datasets = {\n",
    "    \"hobbies\": os.path.join(FIXTURES, \"hobbies\")\n",
    "}\n",
    "\n",
    "\n",
    "def load_data(name, download=True):\n",
    "    \"\"\"\n",
    "    Loads and wrangles the passed in text corpus by name.\n",
    "    If download is specified, this method will download any missing files. \n",
    "    \"\"\"\n",
    "    \n",
    "    # Get the path from the datasets \n",
    "    path = datasets[name]\n",
    "    \n",
    "    # Check if the data exists, otherwise download or raise \n",
    "    if not os.path.exists(path):\n",
    "        if download:\n",
    "            download_all() \n",
    "        else:\n",
    "            raise ValueError((\n",
    "                \"'{}' dataset has not been downloaded, \"\n",
    "                \"use the download.py module to fetch datasets\"\n",
    "            ).format(name))\n",
    "    \n",
    "    # Read the directories in the directory as the categories. \n",
    "    categories = [\n",
    "        cat for cat in os.listdir(path) \n",
    "        if os.path.isdir(os.path.join(path, cat))\n",
    "    ]\n",
    "    \n",
    "    \n",
    "    files  = [] # holds the file names relative to the root \n",
    "    data   = [] # holds the text read from the file \n",
    "    target = [] # holds the string of the category \n",
    "        \n",
    "    # Load the data from the files in the corpus \n",
    "    for cat in categories:\n",
    "        for name in os.listdir(os.path.join(path, cat)):\n",
    "            files.append(os.path.join(path, cat, name))\n",
    "            target.append(cat)\n",
    "            \n",
    "            with open(os.path.join(path, cat, name), 'r') as f:\n",
    "                data.append(f.read())\n",
    "        \n",
    "    \n",
    "    # Return the data bunch for use similar to the newsgroups example\n",
    "    return Bunch(\n",
    "        categories=categories,\n",
    "        files=files,\n",
    "        data=data,\n",
    "        target=target,\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "corpus = load_data('hobbies') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Frequency Distribution Visualization \n",
    "\n",
    "A method for visualizing the frequency of tokens within and across corpora is frequency distribution. A frequency distribution tells us the frequency of each vocabulary item in the text. In general, it could count any kind of observable event. It is a distribution because it tells us how the total number of word tokens in the text are distributed across the vocabulary items."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "from yellowbrick.text.freqdist import FreqDistVisualizer "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the `FreqDistVisualizer` does not perform any normalization or vectorization, and it expects text that has already be count vectorized.\n",
    "\n",
    "We first instantiate a `FreqDistVisualizer` object, and then call `fit()` on that object with the count vectorized documents and the features (i.e. the words from the corpus), which computes the frequency distribution. The visualizer then plots a bar chart of the top 50 most frequent terms in the corpus, with the terms listed along the x-axis and frequency counts depicted at y-axis values. As with other Yellowbrick visualizers, when the user invokes `poof()`, the finalized visualization is shown."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/sklearn/cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n",
      "  \"This module will be removed in 0.20.\", DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "vectorizer = CountVectorizer()\n",
    "docs       = vectorizer.fit_transform(corpus.data)\n",
    "features   = vectorizer.get_feature_names()\n",
    "\n",
    "visualizer = FreqDistVisualizer()\n",
    "visualizer.fit(docs, features)\n",
    "visualizer.poof()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing Stopwords Removal\n",
    "\n",
    "For example, it is interesting to compare the results of the `FreqDistVisualizer` before and after stopwords have been removed from the corpus:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/matplotlib/axes/_axes.py:531: UserWarning: No labelled objects found. Use label='...' kwarg on individual plots.\n",
      "  warnings.warn(\"No labelled objects found. \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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jQ+vXr9egQYPk5uYmX19fhYaGavny5ZKk+Ph49e3bVzabTV5eXurRo4eWLVt2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\nX8NSCc/hAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b235e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vectorizer = CountVectorizer(stopwords='english')\n",
    "docs       = vectorizer.fit_transform(corpus.data)\n",
    "features   = vectorizer.get_feature_names()\n",
    "\n",
    "visualizer = FreqDistVisualizer()\n",
    "visualizer.fit(docs, features)\n",
    "visualizer.poof()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing tokens across corpora\n",
    "\n",
    "It is also interesting to explore the differences in tokens across a corpus. The hobbies corpus that comes with Yellowbrick has already been categorized (try `corpus['categories']`), so let's visually compare the differences in the frequency distributions for two of the categories: _\"cooking\"_ and _\"gaming\"_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "hobby_types = {}\n",
    "\n",
    "for category in corpus['categories']:\n",
    "    texts = []\n",
    "    for idx in range(len(corpus['data'])):\n",
    "        if corpus['target'][idx] == category:\n",
    "            texts.append(corpus['data'][idx])\n",
    "    hobby_types[category] = texts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/matplotlib/axes/_axes.py:531: UserWarning: No labelled objects found. Use label='...' kwarg on individual plots.\n",
      "  warnings.warn(\"No labelled objects found. \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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hkkIDG0uSxq/anWu9smXL3rO+AgDwqLujENegQQNFRkZKkurWratjx47dtm6h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\n4+Hh4eHh4eH5DPl/z51JydrNBwwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10bfb3e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vectorizer = CountVectorizer(stop_words='english')\n",
    "docs       = vectorizer.fit_transform(text for text in hobby_types['cooking'])\n",
    "features   = vectorizer.get_feature_names()\n",
    "\n",
    "visualizer = FreqDistVisualizer()\n",
    "visualizer.fit(docs, features)\n",
    "visualizer.poof()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/matplotlib/axes/_axes.py:531: UserWarning: No labelled objects found. Use label='...' kwarg on individual plots.\n",
      "  warnings.warn(\"No labelled objects found. \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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2m2JjY7Vt2za98MIL2rRpk8LDw5WVlaUTJ05o4cKFevbZZyVJQUFBWrx4sc6c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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108451c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vectorizer = CountVectorizer(stop_words='english')\n",
    "docs       = vectorizer.fit_transform(text for text in hobby_types['gaming'])\n",
    "features   = vectorizer.get_feature_names()\n",
    "\n",
    "visualizer = FreqDistVisualizer()\n",
    "visualizer.fit(docs, features)\n",
    "visualizer.poof()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
